SIVOCS | Preliminary Results of the Survey Analysis

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# SIVOCS | Preliminary Results of the Survey Analysis
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# Respondents

Table with respondent metadata

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# Sample Bias

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<img src="data:image/png;base64,#./table_2.png" width="100%" />

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* Slight bias toward female participants
* Slight bias toward SSH and Natural Sciences
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<img src="data:image/png;base64,#../sample_respondent.svg" width="200%" />
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# Familiarity with SI and Transdisciplinarity

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# Distribution of familiarity with SI among sci. domains

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# Motivation Types

* Relatively consistent results between different sci. domains., slightly lower percentage of motivation to impove human condition among Mathematics, Natural & Engineering Sciences.

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# Intention & Agency

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##### Have you deliberately designed your project so that it might generate an immediate and intended benefit for the general population or a specific non-academic target group?
<img src="data:image/png;base64,#14_SNF_presentation_files/figure-html/unnamed-chunk-13-1.png" width="504" />
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##### Was there an impulse from the non-academic world that motivated you to start the project, namely ...
<img src="data:image/png;base64,#14_SNF_presentation_files/figure-html/unnamed-chunk-14-1.png" width="504" />
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# Transdisciplinary Aspects: Inter-/Transdisciplinary Involvement

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# Transdisciplinary Aspects: Nature of Involvement

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# Transdisciplinary Aspects: Target Group Goals

##### Please indicate whether the following statements fit your project:   Your project has...

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# Regulatory Framework: Open Science/Data Concepts

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# Regulatory Framework: Gender Dimension & Support for Policy-Making

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##### Did your project consider the sex or gender dimension explicitly in your research?
<img src="data:image/png;base64,#14_SNF_presentation_files/figure-html/unnamed-chunk-21-1.png" width="504" />
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##### Did your project aim at supporting evidence-based decision-making of policy-makers? 
<img src="data:image/png;base64,#14_SNF_presentation_files/figure-html/unnamed-chunk-22-1.png" width="504" />

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# Outcome-orientation: Impact Target Group

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# Outcome-orientation: Outcome Intention

##### What kind of change (short- or long-term) did your project intend to bring about in the following target groups or in the general population?

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# Outcome-orientation: Uptake

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##### From your perspective, to what extent were project results taken up by policy-making and/or public administration and/or governmental agencies?

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##### In what way were those results taken up by policy-making and/or public administration and/or governmental agencies?

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# Outcome-orientation: Impact Statements

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# Dissemination and Exploitation: Dissemination Channels

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# Dissemination and Exploitation: Scalability

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# Correlation Matrix, Impact Assessment vs. Motivation

.small[**mot.**: When you designed your project, to what degree were you motivated to…

**impactGr.**: To what degree has your project directly contributed to new or better services, products, processes, or ways of doing things that were targeted towards ...]

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* Motivation to *understand a natural, technical, economic, or social phenomenon better* and *directly address a natural, technical, economic, or social problem* do not correlate well with *direct contribution to new or better services, products, processes, or ways of doing things* of the project.

* Motivation to *improve human condition* shows stat. significant correlations with almost all of the impact statements other than solely academic contribution.

* Strongest positive correlation is between *the benefit to general population* and *motivation to improve human condition* (0.5).

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# Familiarity with SI and Transdisciplinarity vs Impact Assessment, Correlation Matrix

.small[**involv.**: In your research processes, did you actively involve one or more of the following groups(*)?

**policy.uptake**: From your perspective, to what extent were project results taken up by policy-making and/or public administration and/or governmental agencies?

**scalability**: How would you assess in the long term the scalability of the results generated by your project?
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<img src="data:image/png;base64,#14_SNF_presentation_files/figure-html/unnamed-chunk-33-1.png" width="504" />
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* There is almost no stat. significant correlations between up-, out-scalability and inter-/transdisciplinary involvement.
* Deep-scalability correlates with several of the trans-/disciplinary involvement with the highest being the involvement of citizens (0.4).
* Policy uptake also correlates relatively strongly with transdisciplinary involvement in the project, especially when policymakers and civil society organisations involved.

]

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# Motivation Types vs Trans-, Interdisciplinary Involvement, Correlation Matrix

.small[
**involv.**: In your research processes, did you actively involve one or more of the following groups(*)?

**mot.**: When you designed your project, to what degree were you motivated to…
]

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<img src="data:image/png;base64,#14_SNF_presentation_files/figure-html/unnamed-chunk-34-1.png" width="504" />
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* Motivation to *understand a natural, technical, economic, or social phenomenon better* and *directly address a natural, technical, economic, or social problem* do not necessarily correlate with inter-/transdisciplinary involvements.

* Although weakly, motivation to improve human condition/welfare correlates with all of the inter-/transdisciplinary involvements with the strongest ones being *civil society* and *civil society* organisations.

]

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# Transdisciplinary Experience vs. Contribution to SI by Sciencetific Domains

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# Scaleability vs. Transdisciplinarity by Scientific Domains

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# Currently in the Works
    
 * statistical tests
   * non-parametric (@utku: 2-3 beispiele einfügen?)
   * factor analysis (@utku: 1 bespiel einfügen, z.b. outcomes/impact?)

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# Outlook & next steps

* build a statistical models to predict "degree" of SI
  * compile analytical results of survey into a report (part of the final report)
  * ideally: test with more quantitative data
  * publish results in scientific journal